| Line | Haplotype | Population | Frequency (%) | Sample Size | ||
|---|---|---|---|---|---|---|
| 1 | MICA*010-B*46:01 | ![]() | Thailand North East MIC | 14.7 | 255 | |
| 2 | MICA*010-B*15:01 | ![]() | South Korea Seoul MIC | 10.4 | 139 | |
| 3 | MICA*010-B*40 | ![]() | South Korea MIC | 10.3 | 199 | |
| 4 | MICA*010-B*15:07 | ![]() | Argentina Formosa Toba MIC | 9.9 | 94 | |
| 5 | MICA*010-B*52:01 | ![]() | Argentina Formosa Toba MIC | 9.3 | 94 | |
| 6 | MICA*010-B*46:01 | ![]() | China Zhejiang Province Han MIC | 8.0 | 100 | |
| 7 | MICA*010-B*46 | ![]() | China Baotou Han MIC | 6.3 | 104 | |
| 8 | MICA*010-B*15:20 | ![]() | Argentina Formosa Wichi MIC | 6.2 | 42 | |
| 9 | MICA*010-B*15 | ![]() | Brazil Parana Japanese MIC | 5.8 | 190 | |
| 10 | MICA*010-B*46 | ![]() | South Korea MIC | 5.8 | 199 | |
| 11 | MICA*010-B*46:01 | ![]() | South Korea Seoul MIC | 5.8 | 139 | |
| 12 | MICA*010-B*46 | ![]() | Brazil Parana Japanese MIC | 5.0 | 190 | |
| 13 | MICA*010-B*15:08 | ![]() | Argentina Formosa Wichi MIC | 4.8 | 42 | |
| 14 | MICA*010-B*15:01 | ![]() | USA Caucasian MIC pop2 | 4.7 | 242 | |
| 15 | MICA*010-B*15:01 | ![]() | China Zhejiang Province Han MIC | 4.0 | 100 | |
| 16 | MICA*010-B*15 | ![]() | Thailand North East MIC | 3.5 | 255 | |
| 17 | MICA*010-B*15 | ![]() | Brazil Sao Paulo Mixed MIC | 3.3 | 200 | |
| 18 | MICA*010-B*15:01 | ![]() | Spain Murcia MIC | 3.3 | 154 | |
| 19 | MICA*010-B*15:11 | ![]() | China Zhejiang Province Han MIC | 3.0 | 100 | |
| 20 | MICA*010-B*15 | ![]() | Brazil Parana Mixed MIC | 2.9 | 201 | |
| 21 | MICA*010-B*15:01 | ![]() | Spain Majorca MIC | 1.8 | 165 | |
| 22 | MICA*010-B*44:03 | ![]() | USA Caucasian MIC pop2 | 1.5 | 242 | |
| 23 | MICA*010-MICB*005:02 | ![]() | China Guangxi Zhuang MIC | 1.1 | 209 | |
| 24 | MICA*010-B*40 | ![]() | Brazil Parana Japanese MIC | 0.3 | 190 | |
| 25 | MICA*010-MICB*014 | ![]() | China Guangxi Zhuang MIC | 0.3 | 209 | |